The mapping of physiological processes in the body has become an essential resource in medical imaging. Physiological processes can be made visible here with the aid of radioactive tracers, which collect in an organ. To this end radioactive preparations are frequently used, which emit positrons, which are revealed by way of their annihilation with ambient electrons. During annihilation of the positrons pairs of collinear photons with 511 keV energy each are emitted, each reaching a detector. If the detector signals coincide, the revealed photons clearly originate from the same event. Positron emission tomography (PET) recordings of a patient can be generated in this manner.
Recordings can also be made for example using emission tomography (Single Photon Emission Computed Tomography, SPECT).
When recording emission tomography spectra and in particular PET spectra the count rates of the recordings are generally not very high due to coincidence conditions, and to achieve a good statistic efforts have been made to capture all emitted photons, such as for example all 511 keV photons from the positron annihilation. This is difficult as many photons with this energy are scattered in the surrounding tissue. The problem to be resolved is that some of the photons interact in the body before they reach the detector of the emission tomography device. In order to be able to take this interaction into account attenuation factors have to be determined for every event line, in other words the line connecting two detector segments during positron annihilation. The corresponding photon scatter loss is generally referred to as attenuation of the photons, for example of the 511 keV radiation in the tissue.
Efforts have been made in the prior art to compensate for radiation attenuation computationally at a later stage. To this end an attenuation coefficient is associated with each of the individual tissue types. The attenuation coefficient is then used to calculate the actual positron generation rate for each spatial region of the recoding (voxel).
The distribution of tissue types in the body has been determined hitherto mainly by computed tomography (CT) measurements, which allow very precise location of the individual organs.
Various approaches are known in the prior art for carrying out attenuation and scatter correction of the count rate for emission tomography recordings such as PET and SPECT.
On the one hand it is possible to derive the attenuation factors from transmission recordings with external radioactive preparations. Attenuation factors can also be used, which originate from the segmentation of transmission recordings, which were obtained with external radioactive preparations. Segmentation is carried out here to suppress noise before transfer to the emission tomography recording. Attenuation factors are also deployed, which were calculated from a geometric model of the mapped object. Finally attenuation factors are used, which were obtained from transmission recordings with x-ray sources, generally PET/CT and SPECT/CT devices.
With current PET/CT recording devices the determination of attenuation values is principally based on the CT data. More specifically the attenuation factors for each individual voxel are measured first in the attenuation map and integration is then carried out by way of each event line.
It is however not possible to carry out PET and CT measurements simultaneously and therefore at the same site. It is not possible to register both measurements (make them cover one another) without further action. Generally therefore the combination of CT and PET for determining PET attenuation coefficients has significant disadvantages due to the differing recording times of CT recording and PET recording.
The evaluation of magnetic resonance (MR) data would be desirable for determining PET attenuation coefficients. The combination of magnetic resonance and PET measurements has the advantage that these two measurements can be carried out simultaneously and at the same site. With the PET/MR recording devices the MR data can be used to determine the attenuation of 511 keV photons. Like CT measurements MR measurement also provides very precise information about the spatial arrangement of tissue in the body. The attenuation coefficients are associated with tissue regions as a function of the respective tissue type. In other words water has a different attenuation of 511 keV photons from fatty tissue.
The association of attenuation coefficients with tissue regions is however generally very complex. It must be clarified how the MR data has to be processed in order to be able to create an attenuation map, which allows a satisfactory reconstruction of PET events from the PET recording and thus provides a result, which can be compared with CT-based attenuation coefficients.
Attenuation coefficients have been examined in conjunction with neurological PET recordings for example in the following publications.
H Zaidi et al. in “Magnetic resonance imaging-guided attenuation end scatter corrections in three-dimensional brain positron emission tomography”, Med Phys 2003, 30, 937-948, describe MR-based attenuation factors for PET recordings of the head, with segmentation by way of fuzzy cluster technology producing a T1-weighted MR recording. The voxels were interpreted as air, skull, brain and nasal cavities and they were allocated a theoretical, tissue-dependent attenuation coefficient, which was then subjected to Gaussian smoothing. E. Rota Kops et al. in “MRI based attenuation correaction for brain PET images” in: Buzug T M, Holz D, Bongartz J, Kohl-Bareis M, Hartmann U, Weber S, Hrsg., “Advances in Medical Engineering”, Berlin, 2007; 93-97, describe the segmentation of TI-weighted MR recordings in brain, bones, soft tissue and sinuses. The attenuation coefficients, which correspond to the elementary structure and density as well as the photon energy of 511 keV, were associated correspondingly. Attenuation tables with up to four components were produced.
M. Hofmann et al. in “A machine learning approach for determining the PET attenuation map from magnetic resonance images”, IEEE NSS-MIC 2006; 115, describe an approach to automating the identification of differently attenuating tissue regions.
Similarly M. Hofmann at al. in “Attenuation Correction: Method and Validation”, IEEE NSS-MIC 2007, describe the registration of specific MR data in relation to an MR atlas, which is in turn registered with a CT recording. The CT-derived coefficients are then deployed in association with known relationships from local image segments.
For whole body recordings using the PET method in US2008/0135769 a method is described for correcting attenuation in a PET recording. The attenuation coefficients are derived from MR data and the PET recordings are then reworked with the attenuation coefficients.
A storage medium for producing a mapping is known from US2006/006641, being used to produce a nuclear medical image, the atlas comprising a set of magnetic resonance data and a set of correction data in association with the magnetic reference data set.
T. Beyer et al. in “MR-based attenuation correction for torso-PET/MR imaging: pitfalls in mapping MR to CT data”, Nucl. Med. Mol. Imaging, 2008; 35; 1142-6 propose producing a pseudo-CT recording, which is obtained from MR data by adjusting a histogram of MR and CT data.